In order to determine the manner in which
temporal patterns are represented in recurrent
neural networks, networks trained on a vari-
ety of sequence recognition tasks are exam-
ined. Analysis of the state space of unit ac-
tivations allows a direct view of the means em-
ployed by the network to solve a given prob-
lem, and yields insight both into the class of
solutions these networks cfm produce and h o w
these will generalise to sequences outside the
training set. This intuitive approach helps in
assessing the potential of recurrent networks
for a variety of modelling problems.
